1. Technical Field of the Invention
The present invention relates to the field of electronics, and more particularly to a method to detect parked vehicles.
2. Prior Arts
Locating a vacant parking space causes much frustration to motorists. It increases fuel consumption and has a negative impact to the environment. To conserve energy resources and enhance the quality of the environment, it is highly desired to develop a parking-monitoring system, which can transmit substantially real-time parking occupancy data to motorists. Based on the parking occupancy data, a motorist can be guided towards a vacant parking space at destination.
Parking enforcement is an important aspect of city management. The current parking-enforcement system is patrol-based, i.e. parking enforcement officers patrol the streets and/or parking lots to enforce the parking regulations. This operation requires significant amount of man power and also consumes a lot of fuel. It is highly desired to take advantage of the above-mentioned parking-monitoring system and automatically measure the parking time for each monitored parking space.
Both parking monitoring and enforcement are based on the detection of parked vehicles (i.e. parking detection). Because it can monitor a large number of parking spaces simultaneously, a camera is an ideal device for parking detection. Prior arts disclose many camera-based parking-monitoring systems. Bernal et al. (U.S. Patent App. Pub. No. 2013/0265423 A1) disclosed a parking-monitoring system using a background-subtraction algorithm. A parking space is detected as occupied if there is substantial difference between a presently captured image and a background image (i.e. the image of the parking space when it is vacant) within the region of interest (ROI). For each parking space, its ROI is a region in its image that is processed for parking detection.
Background-subtraction algorithm is sensitive to the viewing angle of the camera. When the viewing angle of the camera is small (i.e. the camera is mounted low above the ground), erroneous results may be obtained. FIG. 1A discloses an example. This parking area comprises four parking spaces A1-A4. The image 50 of the parking space A2 is a parallelogram “abcd” (points “c”, “d” not shown). It is substantially occluded by a front-parked vehicle 40a (a vehicle parked immediately in front of the parking space A2, i.e. in the parking space A1). The background-subtraction algorithm will erroneously detect the parking space A2 as occupied.
Background-subtraction algorithm is also sensitive to shadows. When a shadow is cast over a parking space, erroneous results may be obtained. FIG. 1B discloses an example. Suppose the background image was taken when there is no shadow in a parking space A2. At the time of parking detection, a shadow 55 is cast over the parking space A2. The background-subtraction algorithm will erroneously detect the parking space A2 as occupied. Besides viewing angle and shadows, the background-subtraction algorithm is also sensitive to lighting variations and surface conditions of the parking space. A change in lighting (e.g. from a sunny day to a cloudy day) may cause erroneous detection. In addition, a wet, snowy or leafy surface may also cause erroneous detection. In sum, the background-subtraction algorithm is not robust.